Effective Flow Filtering for Botnet Search Space Reduction

Abstract

The use of sophisticated techniques is essential to detect and identify the presence of botnet flows, but these techniques can be expensive in computational and memory resources. A critical first pass is to filter out all traffic that is highly unlikely to be part of a botnet, allowing the more complex algorithms to run over a much smaller set of flows. This paper presents our studies and experience in filtering flows to reduce the botnet search space, and shows that a series of simple filters can provide as much as a 37-fold reduction in the flow set.